相关论文: FRT Regulation in China

Many face recognition systems boost the performance using deep learning models, but only a few researches go into the mechanisms for dealing with online registration. Although we can obtain discriminative facial features through the…

As a startup company in the autonomous driving space, we have undergone four years of painful experiences dealing with a broad spectrum of regulatory requirements. Compared to the software industry norm, which spends 13% of their overall…

Machine learning systems require representations of the real world for training and testing - they require data, and lots of it. Collecting data at scale has logistical and ethical challenges, and synthetic data promises a solution to these…

Contemporary face detection algorithms have to deal with many challenges such as variations in pose, illumination, and scale. A subclass of the face detection problem that has recently gained increasing attention is occluded face detection,…

Face detection is a long-standing challenge in the field of computer vision, with the ultimate goal being to accurately localize human faces in an unconstrained environment. There are significant technical hurdles in making these systems…

Ample research has demonstrated that compliance with data protection principles remains limited on the web and mobile. For example, almost none of the apps on the Google Play Store fulfil the minimum requirements regarding consent under EU…

Radio Frequency Identification (RFID) is a modern communication technology, which provides authentication and identification through a nonphysical contact. Recently, the use of this technology is almost developed in healthcare environments.…

Mixed Reality (MR) devices require a world with always-on sensors and real-time processing applied to their outputs. We have grappled with some of the ethical concerns presented by this scenario, such as bystander privacy issues with…

In identity management system, commonly used biometric recognition system needs attention towards issue of biometric template protection as far as more reliable solution is concerned. In view of this biometric template protection algorithm…

Chinese Remainder Theorem (CRT) is a powerful approach to solve ambiguity resolution related problems such as undersampling frequency estimation and phase unwrapping which are widely applied in localization. Recently, the deterministic…

Biometric systems involve security assurance to make our system highly secured and robust. Nowadays, biometric technology has been fixed into new systems with the aim of enforcing strong privacy and security. Several innovative system have…

[Context and motivation]: Understanding and interpreting regulatory norms and inferring software requirements from them is a critical step towards regulatory compliance, a matter of significant importance in various industrial sectors.…

With the exponential advancement of business technology in recent years, data-driven decision making has become the core of most industries. With the rise of new privacy regulations such as the General Data Protection Regulation in the…

In order to effectively prevent the spread of COVID-19 virus, almost everyone wears a mask during coronavirus epidemic. This almost makes conventional facial recognition technology ineffective in many cases, such as community access…

Bidirectional Encoder Representations from Transformers (BERT) have shown to be a promising way to dramatically improve the performance across various Natural Language Processing tasks [Devlin et al., 2019]. Meanwhile, progress made over…

Face recognition has been extensively studied in computer vision and artificial intelligence communities in recent years. An important issue of face recognition is data privacy, which receives more and more public concerns. As a common…

Recently, deep learning-based methods have reached an excellent performance on License Plate (LP) detection and recognition tasks. However, it is still challenging to build a robust model for Chinese LPs since there are not enough large and…

Federated representation learning (FRL) is a popular personalized federated learning (FL) framework where clients work together to train a common representation while retaining their personalized heads. Existing studies, however, largely…

In recent times, there have been increasing accusations on artificial intelligence systems and algorithms of computer vision of possessing implicit biases. Even though these conversations are more prevalent now and systems are improving by…

Dark patterns have become increasingly pervasive in online choice architectures, encompassing practices like subscription traps, hiding information about fees, pre-selecting options by default, nagging, and drip pricing. Regulators around…